Electric cooperative sharpens forecasts, reduces energy costs

NCEMC decreases forecast generation time from six weeks to just a few hours

With population growth of 16 percent in the past decade (outpacing the US average), North Carolina – the 10th most populous state in the country – has become a magnet for families and businesses drawn to the attractive climate, open spaces and business-friendly environment. That growth is creating increasing demands on the state's electricity infrastructure – demands that are being felt by the North Carolina Electric Membership Corp. (NCEMC).

This group of 26 not-for-profit, member-owned cooperatives provides electricity to more than 950,000 households spanning 93 of the state's 100 counties. To achieve the lowest possible costs and ensure a reliable energy supply, NCEMC creates sophisticated forecasts for short- and long-term horizons for its member cooperatives and regulators. These forecasts are critical because, with few exceptions, energy in the electrical grid cannot be stored – it must be generated as needed and therefore must closely match the current demand. Imbalances can necessitate keeping expensive capital equipment – such as transformers, transmission wires, substations, and even entire generation stations – on standby to meet peak consumption periods. Because approximately 50 percent of NCEMC's power is purchased, the organization needed clear forward visibility to determine its needs in order to negotiate most favorable contractual terms and conditions.

We're making better and faster decisions for the members over the long term. That's translating into a reliable, affordable portfolio of power for North Carolina at lower risk.

Tom Laing
Director of Market Research

Building reliable forecasts

According to Mike Burnette, Vice President for Wholesale Rates, NCEMC gains that visibility by creating hourly and daily forecasts of the power each of the cooperatives would require – encompassing the number of consumers to be served and the energy they will consume, and the amount of energy each cooperative will require on an hourly basis. "We relate the energy-usage history to underlying economic conditions on a county-by-county basis," he said. "Then we examine historical relationships between weather and consumption so we can project what we'll need in the future.

"In the past," Burnette said, "We'd hand off these forecasts to our generation and transmission team, who would convert our forecasts into their own models that simulate what portfolio of resources they need – such as coal and nuclear generation and wholesale purchases to meet the hour-by-hour demand curve. This would affect decisions about contracts and plant construction for decades. Unfortunately, there was a 'forecast gap' that forced them to convert our monthly data into 8,760 hours of forecast data for 30 years."

Tom Laing, NCEMC's Director of Market Research, explained that this gap required significant manual work to reshape monthly data into hourly load curves that the generation and transmission team needed. "It took as many as six weeks to complete, so we didn't do this too often – about once every two years," he said. "This manual process also limited our ability to consider multiple scenarios, which is critical in today's changing environment.

“It was clumsy and complex,” he said. “We clearly needed a way to automate the process.”

"We worked closely with SAS to explore how these products could have a positive impact on our forecasting process," Burnette said. "Before we were hammering a monthly demand forecast into an hourly shape. Now, we have integrated a load-shape process into the demand forecast.

"No longer do we need a team of individuals creating two labor-intensive, time-consuming manual processes," Burnette said. "What once took six weeks can now be done in a few hours."

A significant return for the long term

"We love the ability to forecast hierarchically," said Laing. "We create as many as 100 small area forecasts and are able to combine them for regional and statewide outlooks. To optimize model performance, we specify both hourly and daily demand models, which are combined to provide a robust estimate of hourly and daily peaks. The resulting load shape is then grown from one year to 40 years at all levels of the hierarchy."

The SAS solution has enabled the team to move .5 FTE of resources to other tasks, saving direct expenses. More importantly, armed with a clearer capacity outlook and load demands, NCEMC can secure the lowest-cost power to meet the demand of each member co-op. "We're making better and faster decisions for the members over the long term," Laing said. "That's translating into a reliable, affordable portfolio of power for North Carolina at lower risk – which is, of course, the heart of our mission."

Challenge

Forecast power demands and consumption patterns on an hourly, daily and monthly basis for up to 30-40 years to ensure smart capital and construction decisions and the reliable availability of lower-cost power for more than 950,000 North Carolina households.

Solution

Benefits

Time to generate forecasts decreased from six weeks to just a few hours. Resources required to prepare forecasts declined by .5 FTE. That's translated into faster, smarter and more confident decisions.

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